Triple

T892164
Position Surface form Disambiguated ID Type / Status
Subject Ram E19262 entity
Predicate notableModel P1503 FINISHED
Object Ram 3500 E102363 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ram 3500 | Statement: [Ram, notableModel, Ram 3500]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ram 3500
Context triple: [Ram, notableModel, Ram 3500]
  • A. Ram 3500 chosen
    The Ram 3500 is a heavy-duty full-size pickup truck known for its powerful towing and hauling capabilities, offered under the Ram Trucks brand.
  • B. Ram 2500
    The Ram 2500 is a heavy-duty full-size pickup truck known for its strong towing and hauling capabilities, offered by Ram Trucks for work and recreational use.
  • C. Ram Trucks
    Ram Trucks is an American brand of light to heavy-duty pickup trucks and commercial vehicles known for its powerful performance and rugged design.
  • D. Toyota Tundra
    The Toyota Tundra is a full-size pickup truck known for its durability, strong towing capability, and Toyota’s reputation for reliability.
  • E. GMC Sierra
    The GMC Sierra is a full-size pickup truck known for its powerful performance, upscale features, and role as one of General Motors’ flagship trucks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad0304b081908d4c92bb2beadb81 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a826d4030081909a1c3347228f65c1 completed March 4, 2026, 12:34 p.m.
Created at: March 1, 2026, 7:39 p.m.